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Two-level decomposition algorithm for crew rostering problems with fair working condition

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  • Nishi, Tatsushi
  • Sugiyama, Taichi
  • Inuiguchi, Masahiro
Abstract
A typical railway crew scheduling problem consists of two phases: a crew pairing problem to determine a set of crew duties and a crew rostering problem. The crew rostering problem aims to find a set of rosters that forms workforce assignment of crew duties and rest periods satisfying several working regulations. In this paper, we present a two-level decomposition approach to solve railway crew rostering problem with the objective of fair working condition. To reduce computational efforts, the original problem is decomposed into the upper-level master problem and the lower-level subproblem. The subproblem can be further decomposed into several subproblems for each roster. These problems are iteratively solved by incorporating cuts into the master problem. We show that the relaxed problem of the master problem can be formulated as a uniform parallel machine scheduling problem to minimize makespan, which is NP-hard. An efficient branch-and-bound algorithm is applied to solve the master problem. Effective valid cuts are developed to reduce feasible search space to tighten the duality gap. Using data provided by the railway company, we demonstrate the effectiveness of the proposed method compared with that of constraint programming techniques for large-scale problems through computational experiments.

Suggested Citation

  • Nishi, Tatsushi & Sugiyama, Taichi & Inuiguchi, Masahiro, 2014. "Two-level decomposition algorithm for crew rostering problems with fair working condition," European Journal of Operational Research, Elsevier, vol. 237(2), pages 465-473.
    • Handle: RePEc:eee:ejores:v:237:y:2014:i:2:p:465-473
    DOI: 10.1016/j.ejor.2014.02.010
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    1. Souai, Nadia & Teghem, Jacques, 2009. "Genetic algorithm based approach for the integrated airline crew-pairing and rostering problem," European Journal of Operational Research, Elsevier, vol. 199(3), pages 674-683, December.
    2. Alberto Caprara & Paolo Toth & Daniele Vigo & Matteo Fischetti, 1998. "Modeling and Solving the Crew Rostering Problem," Operations Research, INFORMS, vol. 46(6), pages 820-830, December.
    3. Richard Freling & Ramon Lentink & Albert Wagelmans, 2004. "A Decision Support System for Crew Planning in Passenger Transportation Using a Flexible Branch-and-Price Algorithm," Annals of Operations Research, Springer, vol. 127(1), pages 203-222, March.
    4. Saddoune, Mohammed & Desaulniers, Guy & Elhallaoui, Issmail & Soumis, François, 2011. "Integrated airline crew scheduling: A bi-dynamic constraint aggregation method using neighborhoods," European Journal of Operational Research, Elsevier, vol. 212(3), pages 445-454, August.
    5. Bianco, Lucio & Bielli, Maurizio & Mingozzi, Aristide & Ricciardelli, Salvatore & Spadoni, Massimo, 1992. "A heuristic procedure for the crew rostering problem," European Journal of Operational Research, Elsevier, vol. 58(2), pages 272-283, April.
    6. Maenhout, Broos & Vanhoucke, Mario, 2010. "A hybrid scatter search heuristic for personalized crew rostering in the airline industry," European Journal of Operational Research, Elsevier, vol. 206(1), pages 155-167, October.
    7. ManMohan Sodhi & Stephen Norris, 2004. "A Flexible, Fast, and Optimal Modeling Approach Applied to Crew Rostering at London Underground," Annals of Operations Research, Springer, vol. 127(1), pages 259-281, March.
    8. Meinolf Sellmann & Kyriakos Zervoudakis & Panagiotis Stamatopoulos & Torsten Fahle, 2002. "Crew Assignment via Constraint Programming: Integrating Column Generation and Heuristic Tree Search," Annals of Operations Research, Springer, vol. 115(1), pages 207-225, September.
    9. Medard, Claude P. & Sawhney, Nidhi, 2007. "Airline crew scheduling from planning to operations," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1013-1027, December.
    10. J. N. Hooker, 2007. "Planning and Scheduling by Logic-Based Benders Decomposition," Operations Research, INFORMS, vol. 55(3), pages 588-602, June.
    11. Paola Cappanera & Giorgio Gallo, 2004. "A Multicommodity Flow Approach to the Crew Rostering Problem," Operations Research, INFORMS, vol. 52(4), pages 583-596, August.
    12. Lucic, Panta & Teodorovic, Dusan, 1999. "Simulated annealing for the multi-objective aircrew rostering problem," Transportation Research Part A: Policy and Practice, Elsevier, vol. 33(1), pages 19-45, January.
    13. Michel Gamache & François Soumis & Gérald Marquis & Jacques Desrosiers, 1999. "A Column Generation Approach for Large-Scale Aircrew Rostering Problems," Operations Research, INFORMS, vol. 47(2), pages 247-263, April.
    14. Zeghal, F.M. & Minoux, M., 2006. "Modeling and solving a Crew Assignment Problem in air transportation," European Journal of Operational Research, Elsevier, vol. 175(1), pages 187-209, November.
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    3. Breugem, T. & Dollevoet, T.A.B. & Huisman, D., 2017. "Is Equality always desirable?," Econometric Institute Research Papers EI2017-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Doi, Tsubasa & Nishi, Tatsushi & Voß, Stefan, 2018. "Two-level decomposition-based matheuristic for airline crew rostering problems with fair working time," European Journal of Operational Research, Elsevier, vol. 267(2), pages 428-438.
    5. van Rossum, B.T.C. & Dollevoet, T. & Huisman, D., 2024. "Railway crew planning with fairness over time," European Journal of Operational Research, Elsevier, vol. 318(1), pages 55-70.
    6. Mesquita, Marta & Moz, Margarida & Paias, Ana & Pato, Margarida, 2015. "A decompose-and-fix heuristic based on multi-commodity flow models for driver rostering with days-off pattern," European Journal of Operational Research, Elsevier, vol. 245(2), pages 423-437.
    7. F. Zeynep Sargut & Caner Altuntaş & Dilek Cetin Tulazoğlu, 2017. "Multi-objective integrated acyclic crew rostering and vehicle assignment problem in public bus transportation," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(4), pages 1071-1096, October.
    8. Thomas Breugem & Twan Dollevoet & Dennis Huisman, 2022. "Is Equality Always Desirable? Analyzing the Trade-Off Between Fairness and Attractiveness in Crew Rostering," Management Science, INFORMS, vol. 68(4), pages 2619-2641, April.
    9. Julien Maheut & Jose P. Garcia-Sabater & Julio J. Garcia-Sabater & Sofia Garcia-Manglano, 2024. "Solving the multisite staff planning and scheduling problem in a sheltered employment centre that employs workers with intellectual disabilities by MILP: a Spanish case study," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 32(3), pages 569-591, September.
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